Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022

Background The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021. Aim To comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level. Methods We analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility. Results Omicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9–80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7–3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers’ decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022. Conclusion Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.

Results  cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers' decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022. Conclusion: Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.

Introduction
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VOC) Omicron (Phylogenetic Assignment of Named Global Outbreak (Pango) lineage designation: B.1.1.529), characterised by a large number of mutations in the spike gene, has shown a marked growth advantage over pre-circulating lineages, causing a major upsurge of cases in multiple countries from November 2021 onwards [1]. As Europe was transitioning rapidly from Delta (Pango lineage: B.1.617.2) to Omicron dominance, data on presence and proportion of VOCs among SARS-CoV-2 infections across distinct geographical contexts and over time supported assessments of the current and potential short-term implications for public health.
Here, we robustly assess the temporal expansion of Omicron variant in Italy by analysing data collected during four rapid genomic surveys conducted in the country between 6 December 2021 and 17 January 2022.
Results are combined with data gathered by the Italian Integrated Surveillance System with the aim of estimating the impact of the Omicron spread on the upsurge of SARS-CoV-2 transmission and of hospital admissions.

Genomic surveys and sequencing
Genomic surveys were conducted on 6 and 20 December 2021, and on 3 and 17 January 2022. The initiative involved all 19 Regions and two Autonomous Provinces (APs) of Italy and was coordinated by the National Public Health Institute (Istituto Superiore di Sanità, ISS), in collaboration with the Ministry of Health, the Bruno Kessler Foundation, and 120 laboratories distributed across the country.
On the dates of the surveys, random samples were selected in each Region/AP among infections diagnosed with a real-time reverse-transcription PCR (RT-PCR). The sample size was calculated to enable the detection of circulating SARS-CoV-2 variants with a proportion of at least 5% within each of four macroareas (North-East, North-West, Centre, and South/ Islands) with a 2% precision (Supplementary Material section 1). Samples were subjected to whole genome sequencing (WGS) as the gold standard method for variant detection. Alternatively, results from Sanger or next generation sequencing (NGS) of the whole or partial S-gene were collected. Sequences with insufficient quality for variant assignment were discarded from the analysis.

Assessments of Omicron proportion over time
To robustly assess the temporal expansion of Omicron, the proportion of this variant was estimated in each Region/AP using two alternative approaches. The first used Markov Chain Monte Carlo (MCMC) under the assumption of independence in proportion across Regions/APs and surveys. The second fitted a generalised linear mixed model (GLMM) assuming a random intercept and a random slope for each Region/

Table 3
Results AP; the independent variable was the day when the survey took place (Supplementary Material section 2). A binomial distribution for the identified number of Omicron sequences was assumed in both approaches. The procedures were replicated on data aggregated by macro-area.

Estimation of doubling time and net reproduction number
The approximate number of Omicron cases in each Region/AP over time was obtained by multiplying the estimated local proportion from the surveys by the corresponding number of cases notified to the Italian Integrated Surveillance System. Estimates obtained for the first three survey dates were aggregated at the national level and fitted with an exponential curve having growth rate r. The latter was used to estimate the doubling time of Omicron as T = log(2)/r and the net reproduction number as R = 1 + r × GT, where GT represents the average generation time. In the absence of estimates of GT for Omicron, we considered values between 4 and 8 days, covering a range of estimates for previous lineages [2][3][4][5][6] (Supplementary Material section 3). The same procedure was applied to data collected during the first two surveys only for sensitivity analysis.

Analysis of epidemiological surveillance data
The upsurge of SARS-CoV-2 transmission in Italy due to the Omicron spread was additionally evaluated by estimating daily SARS-CoV-2 net R values using data collected by the Italian Integrated Surveillance System [7]. Separate estimates were obtained from the time series of symptomatic cases by date of symptom onset (sym; R sym ), and from the time series of patients admitted to hospital (hos, R hos ) and to intensive care units (ICU; R ICU ) by date of admission. Estimates of the net reproduction numbers are based on the assumption that the Omicron generation time is comparable to that of pre-circulating strains [2,8,9]. The same generation time was assumed to compute reproduction numbers from time series of symptomatic cases, hospitalisations, and ICU admissions. Methodological details are described in the Supplementary Material section 4. Additional information on data routinely collected within the Italian Integrated Surveillance System and applied case definitions can be found in an earlier report [7].   Estimates of the national proportion ranged on average from 94.6% to 97.8% (Table 2).

Results
Results for the four surveys are reported in Figure 1, and in Tables 1 and 3. Corresponding proportion estimates are reported in Table 2.
By using proportion estimates retrieved for the first three dates, we estimated an average daily exponential growth rate r for new Omicron infections of 0.22-0.26 days − 1 , corresponding to an average doubling time of 2.7-3.3 days and reproduction numbers in the range 1.86-2.04 and 2.73-3.08, when a generation time of 4 and 8 days was assumed respectively (Table 2). Similar estimates were obtained when the exponential growth was fitted on the first two surveys only (Supplementary  Table S2).
We note that, despite the decrease in Delta proportion, the average total number of estimated Delta cases also increased in the observation period from 9,336-9,458 on 6 December 2021, to 13,455-15,701 on 3 January 2022 (Supplementary Table S1 and Figure 2). In the subsequent period, Delta cases decreased to 1,844-4,521 on 17 January.
The impact of Omicron expansion on the overall SARS-CoV-2 circulation was quantified by estimating reproduction numbers from the time series of cases recorded by the Italian Integrated Surveillance System. We found that R sym increased from 1.15 (95% credible interval (CrI): 1.15-1.15) on 6 December 2021 to a peak of 1.83 (95%CrI: 1.83-1.84) on 28 December ( Figure  3). R hos increased from 1.14 (95%CrI: 1.12-1.18) on 6 December 2021, to a peak of 1.36 (95%CrI: 1.33-1.38) on 29 December 2021. In contrast, R ICU did not show a clear temporal trend throughout December 2021, with mean estimates ranging between 0.93 and 1.21.
However, a progressive decline of all reproduction numbers was observed in the first weeks of 2022, yielding their mean estimates under the epidemic threshold of 1 between 10 and 16 January.

Discussion
Omicron was first identified in Italy in the second half of November 2021 [10]. Four genomic surveys were successively conducted to evaluate the progressive spread of the variant in the country. The presented results show that Omicron variant (BA.1 subvariant at that time) became dominant across the Italian territory in less than 1 month, significantly increasing SARS-CoV-2 transmission.
Our estimates for the doubling time (2.7-3.3 days) are in agreement with those obtained in other countries [11,12].  [13,14]) and behaviour change had a chance to significantly affect transmission. Notably, changes in contact patterns due to the Christmas holidays may have had an effect that is hard to quantify.
The selective advantage of Omicron over Delta may be explained by increased transmissibility, partial immune escape, or a combination of both [15]. Early evidence from statistical analysis of reinfections and breakthrough infections suggested a marked capability of escape from natural and vaccine-acquired immunity [11,[16][17][18][19]. However, further efforts are needed to quantify the relative transmissibility of Omicron compared with Delta, and its inherent capacity to cause severe disease, which is key to evaluate potential changes in COVID-19 burden potentially led by this and the progressive waning of immunity.
The lower increase of reproduction numbers associated to hospital admissions and the stable value of those from ICU admissions may suggest, under the epidemiological conditions observed in late 2021, a reduced severity of Omicron compared with Delta. However, while only partially protected against infection, individuals who received at least two vaccine doses were substantially protected against severe outcomes [20,21]. It is therefore likely that the lower disease severity observed in populations during the Omicron wave can be partially ascribed to the protection conferred by vaccination and/or prior infection [22,23], explaining

Figure 3
The impact of Omicron spread on SARS-CoV-2 circulation, Italy, December 2021-January 2022 A. 03  A. Time series of total number of notified and symptomatic cases by date of notification and symptom onset (moving average over 7 days), respectively. The number of symptomatic cases by date of symptom onset is shown only for data consolidated on 21 January 2022.
B. Time series of total number of cases admitted to hospital and to ICU, by date of admission (moving average over 7 days).
C. Net reproduction numbers Rt for symptomatic cases, cases admitted to hospital and to ICU, respectively in yellow, blue and red. The solid line represents the mean of the estimated posterior distribution, and the shaded areas delimit 95% credible intervals.
The yellow and blue dashed vertical lines represent the days at which the net reproduction numbers for symptomatic and hospitalised cases respectively reach their peak values, as shown in panel C.
the large decoupling between identified cases and hospitalised individuals.
Marked changes in the ascertainment rate of SARS-CoV-2 infections may have also occurred during the study period due to the brisk increase of identified cases and the consequent saturation of the testing system, the reduced likelihood of test-seeking given the infection, and the possible increase of voluntary testing in preparation for gatherings during Christmas and New Year's holidays [24]. On the other hand, the widespread transmission of Omicron observed throughout January 2022 could have inflated the number of patients admitted to hospital and ICU with a positive test for SARS-CoV-2 infection but with a different primary reason for hospitalisation. Changes in the ascertainment rate of SARS-CoV-2 infection and COVID-19 patients should have a limited impact on the estimated proportion of circulating lineages, and on the growth rate of Omicron infections. However, they may have affected estimates of the reproduction number from different data sources during the replacement of pre-circulating linages by Omicron. All these factors prevented us to quantify the relative risk of hospitalisation and of ICU admission for Omicron compared with Delta.
Of note, we estimate that the total number of Delta cases increased over December 2021, suggesting that a considerable fraction of hospital patients recorded in early January could be attributed to Delta. As such, continued monitoring of Delta proportion among severe cases was recommended.
The four daily surveys were based on relatively small sample sizes and, despite the randomisation of sampling for genomic sequencing, biases due to the presence of large clusters of cases in a region cannot be excluded. Moreover, estimates of the net reproduction numbers are based on the assumption that the Omicron generation time is comparable to that of precirculating strains, as suggested by recent estimates for the Italian context [8,9].
Efforts combining genomic and epidemiological surveillance for tracking circulating variants and analysing epidemiological trends at the population level are of the utmost importance to support public health responses and improve system preparedness for future epidemic threats.

Ethical statement
Ethical approval for sequencing SARS-CoV-2 genomes on clinical samples was obtained by ISS (ref. PRE BIO CE n.26259, July 29, 2020).